Clusteval logo ClustEval clustering evaluation framework

Which parameter sets lead to the optimal clustering quality?

Please choose a clustering quality measure:
Program Best quality Parameter set Clustering
CLARA 0.0 metric=euclidean
k=107
samples=20
Clustering
Self Organizing Maps 0.0 x=183
y=150
Clustering
Spectral Clustering 0.0 k=8 Clustering
clusterdp 0.0 k=16
dc=3.0912
Clustering
HDBSCAN 0.0 minPts=6
k=2
Clustering
AGNES 0.0 method=average
metric=euclidean
k=137
Clustering
c-Means 0.0 k=229
m=1.5
Clustering
k-Medoids (PAM) 0.0 k=88 Clustering
DIANA 0.0 metric=euclidean
k=182
Clustering
DBSCAN 0.0 eps=1.8768
MinPts=191
Clustering
Hierarchical Clustering 0.0 method=single
k=22
Clustering
fanny 0.0 k=95
membexp=2.0
Clustering
k-Means 0.0 k=65
nstart=10
Clustering
DensityCut 0.0 alpha=0.08035714285714285
K=3
Clustering
clusterONE 0.502 s=241
d=1.0
Clustering
Affinity Propagation 0.062 dampfact=0.9175
preference=2.484
maxits=4250
convits=500
Clustering
Markov Clustering 0.502 I=7.104604604604605 Clustering
Transitivity Clustering 0.0 T=3.2655855855855855 Clustering
MCODE 0.021 v=0.6
cutoff=3.036
haircut=F
fluff=T
Clustering